31 results about "CTD" patented technology

The invention discloses an XBT-T5 observation data deviation analysis and temperature correction method, and relates to the technical field of ocean observation, and the method comprises the steps: obtaining the original temperature observation data of a target sea area based on an XBT-T5 front-end temperature sensor, calculating the depth, generating a temperature-depth profile, and constructing a temperature-depth database in combination with historical depth observation archive data; the method comprises the following steps: synchronously acquiring temperature and depth data by using a CTD temperature-salinity-depth instrument, and carrying out association pairing with a temperature-depth database to generate an XBT-T5 observation data deviation field under the same spatial-temporal scale; based on generation of an XBT-T5 observation data deviation field under the same spatial-temporal scale, designing a dual-channel adaptive encoder, and constructing a temperature-depth collaborative correction model; and according to the temperature-depth collaborative correction model, coupling the temperature-depth database and generating an XBT-T5 observation data deviation field under the same spatial-temporal scale, thereby realizing XBT-T5 observation data deviation analysis and temperature correction. The method improves the quality and application value of observation data.

This invention relates to a data processing system for CTD (Conductivity, Temperature, Depth) instrument observations, comprising: building a fully domestically developed technology foundation, employing a combination of Spring Boot, MyBatis-Plus, DM database, and Vue3 to achieve domestic adaptation of the front-end, back-end, and database; incrementally accessing and storing raw CTD data files based on the technology foundation, generating dual traceability identifiers of FileInfoID and DataID; performing multi-step sequential processing on the stored data, including zero-error correction, outlier filtering, data smoothing, salt density and acoustic calculation, and standard file generation, with each step's algorithm optimized for the characteristics of domestically produced CTD data; storing raw data, intermediate data, and output data through a multi-level data table design, utilizing traceability identifiers to achieve full-process correlation and traceability, and providing visual display and standardized output. This invention achieves fully domestic processing from data access to output, effectively improving the accuracy and traceability of data processing and ensuring marine data security.

The application relates to the technical field of marine environment monitoring, and discloses a marine environment multi-parameter monitoring buoy, which comprises a base, a CTD sensor arranged at the underwater position of the base and internally integrated with a wave sensor; a support, a wind direction and speed sensor, an air pressure sensor and an air temperature and humidity sensor being mounted at the top of the support; a photovoltaic panel angle adjusting module; a photovoltaic panel frame; a cleaning assembly; and a self-adaptive angle adjusting module. The longitudinal rotating scraper is separated from seawater after rotating, so that the long-term immersion of the scraper in seawater is avoided, the corrosion of the scraper is accelerated, meanwhile, the biological organisms such as barnacles in the seawater cannot be attached and grown on the surface of the scraper, and the service life of the scraper is prolonged. The space posture of the mounting disc is adjusted through the cooperation of the telescopic adjustment, the corresponding push rod is driven to independently extend and retract, the mounting disc always keeps a dynamic horizontal state when the buoy swings with waves, and the requirements of the meteorological observation specification on the wind direction and speed measurement accuracy are met.

The invention discloses a coral reef ecosystem community carbon sequestration evaluation method based on a Lagrange drift trajectory, and belongs to the field of marine ecological environment monitoring and carbon cycle research. The device comprises a drift tracking module, a CTD module, a hydrochemical parameter acquisition module, a depth instrument, a waterproof system and a buoyancy system, all the modules are integrated in the waterproof system, the buoyancy system is connected with the exterior of the waterproof system, and the modules are in signal connection to realize data transmission; according to the method, a Lagrange drift path and a time interval are recorded through the drift tracking module, the CTD module collects the temperature and salinity of a water body, the hydrochemical parameter collection module obtains total alkalinity and dissolved inorganic carbon and calculates the variable quantity of the total alkalinity and the dissolved inorganic carbon, and the depth instrument monitors the average water depth; the COexchange flux is calculated in combination with meteorological data, and then the net calcification rate and the net photosynthesis rate are obtained through a preset formula.

The application discloses a multilayer synchronous micro-plastic observation system and method based on ocean front tracking, which comprises a front tracking ship and a cross-front observation ship; the front tracking ship is provided with a Manta trawl net and a sampling pump; and the cross-front observation ship is provided with an ADCP and a CTD. The method comprises the following steps: selecting one or more voyage sections on the front, performing micro-plastic tracking voyage along the front direction by the front tracking ship, collecting micro-plastic particles in the surface layer and vertical section, performing cross-front voyage perpendicular to the front direction by the cross-front observation ship, measuring key physical parameters of the front intensity, counting the micro-plastic abundance of each voyage section, calculating the salt density horizontal gradient based on interpolation, calculating the horizontal flow velocity divergence, and then performing observation data fitting to obtain the corresponding relationship between the front intensity and the micro-plastic abundance. The application realizes the collection of micro-plastics at the ocean front and the observation of physical elements by synchronously collecting key data through the double-ship system, and establishes the influence and action relationship of the ocean front physical elements on the micro-plastics.

The invention relates to a water mass classification accuracy judgment method, and the method comprises the steps: obtaining target sea area CTD observation data, and carrying out the standardization processing, and obtaining the standardized data; based on a K-means + + clustering algorithm, spatial clustering analysis is carried out on the standardized data with the multi-element features, the optimal cluster number is screened out, and spatial distribution of the water mass is obtained; combining the spatial distribution of the water mass with the multi-element features, and determining the category and spatial distribution of the water mass and the three-dimensional division result of the feature range of each element according to the optimal cluster number; and according to a principal component analysis method, the separation degree and the concentration degree of each type of water mass in a principal component space are detected so as to evaluate the accuracy of a three-dimensional division result. According to the method, three-dimensional water mass classification is realized, the space structure of the water mass in the target sea area can be comprehensively disclosed, the classification accuracy is objectively judged, and the influence of subjective factors on a water mass division result is effectively reduced.

This invention provides a positioning method for the main buoy of an acoustic underwater mooring, relating to the field of acoustic underwater mooring main buoy positioning technology. Specifically, it includes the following steps: using a pressure sensor to measure the pressure at the location of the main buoy, and then calculating the actual depth and settling displacement of the main buoy; indirectly calculating the sound velocity in seawater using a segmented CTD (Cyclic Transmission Device) on the mooring system, and using the sound velocity to calculate the distance between the main buoy and the anchored weight, thereby indirectly calculating the horizontal offset of the main buoy; measuring the seawater current velocity vector in the water area where the main buoy is located using an ADCP (Advanced Directional Phase Array); and installing a current-facing tail fin at the tail of the main buoy to ensure that the main buoy always faces the current, with the opposite direction of the seawater flow being the direction of the main buoy. The technical solution of this invention overcomes the problem of existing technologies being unable to accurately position the main buoy of an acoustic underwater mooring.

The present application relates to the technical field of offshore wind farm area marine environment monitoring, and discloses a kind of offshore wind farm wide area environment panoramic perception method and system, comprising: S1, in the target area of offshore wind farm layout seabed bottom type comprehensive observation equipment and low-altitude meteorological observation equipment;The seabed bottom type comprehensive observation equipment includes acoustic Doppler current profiler, tide gauge, temperature salinity depth instrument, and the low-altitude meteorological observation equipment includes weather station, wind radar;S2, through seabed bottom type comprehensive observation equipment, low-altitude meteorological observation equipment acquisition field data, through meteorological remote sensing satellite acquisition remote sensing data, remote sensing data is inverted to obtain remote sensing inversion data, and field data and remote sensing inversion data are transmitted to software processing platform etc.;The method and system can realize the collaborative collection of space-time-sea multidimensional data, accurate processing and fusion prediction, improve the comprehensiveness and accuracy of offshore wind farm environment perception.

The invention belongs to the technical field of ocean monitoring and sensors, and discloses a measuring method and device for correcting the actual ocean shallow profile temperature. The method comprises the following steps: obtaining the real emissivity of a calm water surface; inputting the wind speed wave height of the seawater in the actual sea condition, the wind speed of the air and the obtained actual emissivity of the calm water surface into a Monte Carlo emissivity correction model, outputting the corrected actual sea condition seawater emissivity, and taking the corrected actual sea condition seawater emissivity as a parameter for measuring the actual water surface temperature by a second IR infrared thermometer; and based on the obtained modified parameters of the real water surface temperature measured by the second IR infrared thermometer, carrying out actual sea surface temperature measurement by arranging thermosensitive chains with different scales. The method is obviously superior to the prior art (the satellite is 0.3-1K, the shipborne infrared is 0.05-0.1 K, and the anchor system CTD is 0.002 K and is larger than or equal to 5cm on average).

The application discloses a temperature time domain alignment and error compensation method of a temperature-salinity-depth instrument, and relates to the technical field of temperature-salinity-depth instrument measurement, and the specific steps are as follows: firstly, the original temperature sequence of the temperature-salinity-depth instrument and the temperature true value sequence of a high-precision reference instrument are synchronously collected, time domain alignment of the original temperature sequence is completed through root mean square error minimization search, based on the aligned temperature sequence, the first-order temperature change rate and the second-order temperature change rate dynamic characteristics are calculated, and a multi-dimensional feature vector is constructed; the actual residual error of the aligned temperature sequence and the temperature true value sequence is taken as a learning target, a random forest nonlinear regression model is trained, a residual error compensation amount is fitted, and a final corrected temperature sequence is output. Compared with the traditional linear model method, the root mean square error of temperature measurement of the model method is significantly reduced, the nonlinear dynamic error under the strong dynamic variable temperature working condition is effectively inhibited, the measurement precision and the robustness of the temperature-salinity-depth instrument are improved, and the application requirements of ocean observation are met.

This invention relates to the field of marine acoustic modeling and underwater acoustic environment forecasting, and in particular to an integrated method for dynamic extraction of Kuroshio frontal features and sound field modeling based on publicly available data. Through the integrated design of dynamic encryption of publicly available data, frontal feature quantization and PINNs modeling, this invention greatly reduces the sound field forecasting error of Kuroshio frontal regions and reduces the cost of CTD measured data.

The present application relates to the technical field of marine observation and data processing, in particular to a kind of Yellow Sea cold water mass submesoscale structure observation method and its observation system, comprising the following steps: step one: data acquisition;Obtain multiple profile data by the temperature-salinity-depth instrument carried by wave energy profile float, import profile data into observation system, form profile data txt file, as raw data;Step two: feature recognition and three-dimensional reconstruction;Raw data is processed using python program, to obtain temperature-depth-time array and salinity-depth-time array;Feature recognition, analysis and reconstruction of three-dimensional structure of submesoscale phenomenon are carried out jointly, and the observation of the submesoscale structure of the Yellow Sea cold water mass is realized through the reconstructed three-dimensional structure.The present application realizes the dynamic monitoring of the boundary submesoscale process of the Yellow Sea cold water mass by integrating wave energy profile float and satellite remote sensing technology.

The invention relates to the technical field of ocean internal wave monitoring, and discloses an internal wave inversion method and system based on high-frequency tide level data and satellite remote sensing fusion, and the method comprises the steps: S1, collecting SAR satellite remote sensing data, five-minute sampling interval tide level data, and CTD density profile data, and carrying out the preprocessing; s2, performing space-time alignment on SAR satellite remote sensing data, 5-minute sampling interval tide level data and CTD density profile data; s3, variational mode decomposition is adopted, the preprocessed five-minute sampling interval tide level data are decomposed, and internal wave characteristic modes and the like are screened; according to the method and the system, the spatial resolution of high-precision inversion of multiple parameters such as amplitude, period, propagation speed, direction and energy dissipation is improved to ten meters, the time resolution is optimized to be within one day, the amplitude measurement precision is improved to 0.1 meter, and the method and the system are remarkably superior to the internal wave amplitude measurement precision and the time resolution of an existing SAR satellite.

The invention discloses a temperature time domain alignment and error compensation method for a temperature-salinity-depth instrument, and relates to the technical field of temperature-salinity-depth instrument measurement, and the method comprises the following specific steps: firstly, synchronously collecting an original temperature sequence of the temperature-salinity-depth instrument and a temperature truth value sequence of a high-precision reference instrument, and carrying out the minimum search of a root-mean-square error; time domain alignment of the original temperature sequence is completed, dynamic features of a first-order temperature change rate and a second-order temperature change rate are calculated based on the aligned temperature sequence, and a multi-dimensional feature vector is constructed; and training a random forest nonlinear regression model by taking an actual residual error of the aligned temperature sequence and the temperature truth value sequence as a learning target, fitting a residual error compensation amount, and outputting a final corrected temperature sequence. Compared with a traditional linear model method, the model method provided by the invention has the advantages that the root-mean-square error of temperature measurement is obviously reduced, the nonlinear dynamic error under a strong dynamic temperature change working condition is effectively inhibited, the measurement precision and robustness of the thermohaline depth gauge are improved, and the application requirements of ocean observation are met.

The application relates to the technical field of instrument error monitoring, and discloses an environmental monitoring instrument tendency error analysis system which comprises a multidimensional acquisition module and an intelligent analysis module. The thermosalinograph tendency error analysis system obtains the conductivity data, temperature data and water depth data of a measured water body through the multidimensional acquisition module, classifies and forms a data set, the intelligent analysis module analyzes the time difference between different physical parameters, generates a time difference data set, analyzes the fluctuation range of different physical parameters, generates a fluctuation data set, quickly locates the measurement deviation, the intelligent analysis module analyzes the authenticity of each measurement result, generates a credibility index, dynamically evaluates the credibility of single measurement, can adapt to the monitoring requirements of more complex environments, accurately diagnoses the error source, the intelligent analysis module sets a fixed range threshold, evaluates the influence factors leading to the thermosalinograph tendency error and the authenticity of the measurement result, and outputs corresponding management suggestions, and the automatic operation and maintenance has high practicability.

The present application belongs to the field of ocean observation technology, and relates to a CTD circuit board mounting structure, a CTD and an ocean observation system. The support column is connected between the circuit board mounting block one and the circuit board mounting block two, and can rigidly connect the circuit board mounting block one, the circuit board mounting block two and the circuit board together to form a whole, effectively reducing the stress of the circuit board when vibrating and improving the reliability of the circuit board when working. Meanwhile, the rubber shock absorber outside the circuit board mounting block one and / or the circuit board mounting block two can reduce the axial vibration of the CTD circuit board on the CTD circuit board mounting structure. The outer periphery of the circuit board mounting block one and the circuit board mounting block two is simultaneously provided with a buffer sealing ring, which can reduce the circumferential vibration of the CTD circuit board on the CTD circuit board mounting structure. The buffer sealing ring cooperates with the rubber shock absorber to realize all-around shock absorption and simple installation of the circuit board, and long-term reliable observation of ocean hydrological information can be realized.

The invention provides a ship-borne temperature and salt drag chain observation method and system based on adaptive sampling, and the method comprises the steps: collecting the CTD data of a drag chain, the ship-borne ADCP data and satellite remote sensing data, constructing a multi-source data set, carrying out the assimilation processing of the multi-source data set, and generating a real-time environment field; based on the real-time environment field, ocean key area identification is carried out; a control scheme of the shipborne temperature and salt drag chain is generated in a self-adaptive mode based on the ocean key area recognition result; based on the control scheme, the sampling frequency, form and position of the shipborne thermohaline drag chain are dynamically adjusted, and the optimal ocean thermohaline observation result is obtained. According to the technical scheme, active and accurate observation of the sudden ocean process is achieved, and the intelligence and automation level of observation activities is improved.

The utility model discloses a deep sea subsurface buoy system suitable for fine observation of a bottom boundary layer, which comprises a seabed base, a plurality of single-point flow velocity observation units and a main floating body which are sequentially connected from bottom to top, the plurality of single-point flow velocity observation units are arranged between the seabed base and the main floating body along the tensile cable, and each single-point flow velocity observation unit is integrated with a deepwater single-point current meter and a CTD; an acoustic Doppler flow velocity profiler is installed in the main floating body, and the acoustic Doppler flow velocity profiler, an ADV, a CTD and a double-parallel acoustic releaser are integrated on the seabed base. According to the utility model, an observation blind area is eliminated through structure optimization, and a core area (5-10m) of a bottom boundary layer can be brought into an observation range; multiple observation units with vertical spacing can capture full-water-depth ocean current change details, and the data resolution is improved; due to the arrangement of the double parallel acoustic releasers, the equipment reliability is improved, and the risk of recovery failure is effectively reduced; and long-term continuous observation can be realized.

This invention discloses a siltation early warning method based on the fusion of towed sonar and multi-source hydrological parameters, belonging to the field of underwater topographic monitoring and engineering safety early warning technology. The method first plans the survey lines for the target area and simultaneously collects multibeam sonar bathymetry data, CTD multi-parameter data, platform attitude data, tow cable status data, positioning and navigation data, and time synchronization information during towed platform operation. Then, it performs time alignment, outlier removal, missing value compensation, and noise suppression on the multi-source data. A sound velocity profile is constructed based on the CTD multi-parameter data, and the sound velocity of the multibeam sonar bathymetry data is corrected. Geometric compensation is also performed by combining platform attitude data, tow cable status data, and positioning and navigation data. Finally, the corrected bathymetry data is... The results are mapped to a preset coordinate system to construct an underwater cross-section model, a grid elevation model, or a bed sediment point cloud model for the current time period. Historical baseline models are retrieved for coordinate unification, overlapping area identification, and adaptive registration. Based on this, elevation difference analysis, slope change analysis, regional thickness statistics, and calculations of sediment thickness, changed area, and sediment volume are performed. Furthermore, short-term trend predictions are made by combining historical observations from multiple time periods with environmental driving factors such as flow velocity, tide level, temperature, salinity, turbidity, and sediment content. Finally, a warning level is generated based on a risk threshold, and warning information is output. This invention improves the comparability of multi-time period towed sonar measurement results and the accuracy of sediment identification, enabling continuous monitoring, quantitative analysis, and proactive warning of bed sedimentation status in target areas. It is applicable to port channels, inland waterways, estuaries, reservoir areas, and near-shore engineering areas.

The invention provides a motion compensation device of CTD equipment, which comprises a motion module, a sensing module and a control module, and the motion module comprises an axial motion unit and a radial motion unit. The sensor module senses the underwater rotation state and the real-time attitude angle of the CTD equipment, and the control module controls the axial movement unit to rotate reversely according to the rotation state of the CTD equipment, so that the axial movement speed of the CTD equipment tends to be zero; and controlling the radial motion unit to operate according to the real-time attitude angle of the CTD equipment, and performing closed-loop adjustment on the real-time attitude angle of the CTD equipment to a specific threshold range. Underwater rotation and inclination of the CTD equipment are adjusted and compensated through the motion compensation device, so that the CTD equipment is in a stable state underwater, the problem of damage caused by continuous rotation of a steel cable is solved, and the problem of measurement misalignment of the CTD equipment caused by inconsistent theoretical lowering depth and actual depth of the CTD equipment is solved.

A marine environment observation data quality control method based on a disposable temperature-salinity-depth meter belongs to the technical field of marine observation, and comprises the following steps: step 1, carrying out range correction on observation data; step 2, performing surface transient response correction on the observation data; step 3, performing peak detection correction on the observation data; 4, performing vertical gradient detection correction on the observation data; 5, performing systematic depth deviation correction on the observation data; step 6, carrying out ocean physical law constraint correction on the observation data; and 7, carrying out statistical analysis constraint correction on the observation data. According to the method, the seawater temperature, salinity and depth observation results of the disposable temperature-salinity-depth instrument are corrected, and the reliability of the marine environment observation results of the disposable temperature-salinity-depth instrument can be effectively improved.

The invention relates to the technical field of ocean observation equipment, in particular to a self-adaptive sampling temperature-salinity-depth instrument based on pattern recognition and a control method thereof.The self-adaptive sampling temperature-salinity-depth instrument comprises a pressure-resistant bin, an inner cavity is formed in the pressure-resistant bin, a fixing structural part is arranged in the inner cavity, and the fixing structural part is used for installing a lithium battery and a circuit board; the two ends of the pressure-resistant bin are connected with a head end cover and a tail end cover respectively, and a watertight connector is installed on the head end cover. The tail end is provided with a pressure sensor, a temperature sensor and a conductivity sensor. The temperature-salinity-depth instrument can perform pattern recognition on ocean phenomena according to temperature-salinity data and dynamically adjust the sampling frequency according to a recognition result, so that the reliability and the energy efficiency ratio of measured data are improved; by dynamically adjusting the sampling strategy, 53% of data redundancy is reduced and the endurance of equipment is prolonged by more than 40% on the premise of ensuring that the internal wave event capture rate is greater than or equal to 82%, so that the method is suitable for long-term ocean monitoring scenes.

This invention provides a towed CTD (conductivity, temperature, and depth) measurement system for vertical profile measurement, comprising a deck unit and a winch unit respectively installed on a vessel. The winch unit tows a towed fish via a cable. The observation method of the towed CTD measurement system for vertical profile measurement involves operators preset the parameters for the winch unit to control the lowering or raising of the towed fish, and the towed fish is automatically deployed below the water surface while the vessel is underway. This towed CTD measurement system for vertical profile measurement uses a tugboat to tow the underwater observation system, which is connected to the tugboat by a cable. The underwater observation system carries sensors to measure underwater environmental elements. The towed observation system controls the ascent, descent, and navigation trajectory of the underwater observation system during vessel navigation, enabling multi-parameter ocean vertical profile observation. It features non-interference with vessel navigation, real-time, and simultaneous multi-element observation.

This invention discloses an intelligent CTD sampling control method and system combining tidal current prediction, relating to the field of marine observation technology. The method includes: generating tidal current predictions by fusing historical tidal elements and numerical model outputs, and planning candidate sampling windows; real-time acquisition of multi-source observation data to form standardized observation vectors, calculating the deviation from the predicted values ​​and fusing the vertical shear force intensity factor to perform rolling corrections on the predictions and update the sampling windows; comparing real-time observation data with safety thresholds to generate operational access instructions, issuing control instructions under permissible conditions, and dynamically adjusting sampling parameters and triggering resampling based on profile data quality coefficients; synchronously monitoring abnormal events, triggering emergency recovery, and deferring the task to subsequent candidate windows. By constructing intelligent closed-loop control, introducing vertical shear force early warning, and a parallel processing architecture, adaptive, highly safe, and highly reliable CTD sampling operations under complex sea conditions are achieved.

The invention relates to the technical field of ocean observation and data processing, in particular to an observation method and an observation system of a Yellow Sea cold water mass sub-mesoscale structure. The method comprises the following steps: acquiring a plurality of profile data through a temperature-salinity-depth instrument carried by a wave energy profile buoy, and importing the profile data into an observation system to form a txt file of the profile data as original data; 2, performing feature recognition and three-dimensional reconstruction; processing the original data by adopting a python program to obtain a temperature-depth-time array and a salinity-depth-time array; and carrying out feature recognition in combination, analyzing and reconstructing a three-dimensional structure of a sub-mesoscale phenomenon, and observing the sub-mesoscale structure of the Yellow Sea cold water mass through the reconstructed three-dimensional structure. By integrating the wave energy profile buoy and the satellite remote sensing technology, dynamic monitoring of the Yellow Sea cold water mass boundary sub-mesoscale process is achieved.

The application discloses a seabed sulfide ore body structure wideband seismic constrained inversion imaging method and belongs to the field of marine seismic detection. The application aims at the current seabed sulfide ore body structure detection problem, is based on wideband near-bottom vertical cable seismic detection data, uses a compressed sensing reconstruction method to overcome the data missing problem caused by the influence of the instrument itself, other carried equipment and environmental conditions such as sea waves, improves the subsequent processing accuracy, then constructs an initial constrained smooth velocity model based on rock sample physical property measurement, electrical detection, a plurality of station CTD and other multi-source data, further proposes a multi-step frequency damping multi-scale full waveform inversion velocity modeling method, and uses wave field illumination to correct the model in the iterative inversion, realizes high-resolution imaging of the seabed sulfide ore body from the outline to the details. The application proposes an optimization scheme of seabed sulfide seismic imaging from the angles of data accuracy, initial model construction and inversion method technology, and can effectively improve the accuracy of sulfide ore body structure imaging.

This utility model discloses a deployment and retrieval protection device for CTD seawater sampling equipment, including a sampling component. A connecting plate is mounted on the sampling component, and several connecting columns are fixedly connected to one side of the connecting plate. These connecting columns are arranged in an equally spaced array, and a fixing ring is fixedly connected to one end of each connecting column, forming a connecting groove between the connecting column and the fixing ring. A fixing plate is positioned directly above the fixing ring, and two sets of connecting hooks are arranged on one side of the fixing plate, symmetrically distributed about the central axis of the fixing plate. This deployment and retrieval protection device for CTD seawater sampling equipment addresses the potential impact of ocean currents, wind, and waves on the equipment, significantly reducing equipment swaying during retrieval and greatly decreasing the probability of equipment damage or loss of control. This increases the protection of the equipment and prevents interference with the accuracy of subsequent data.

This invention proposes a deep learning-based CTD cross-section data interpolation and reconstruction method, comprising: a data preprocessing module for extracting effective cross-section data from raw CTD measurement data and performing quality control and standardization; a model building module that utilizes a deep learning model to automatically learn the spatial structural features of CTD data and the nonlinear relationships between multiple variables, enabling more accurate recovery of complex hydrological feature changes and improving data reconstruction accuracy, especially in highly variable areas such as ocean fronts and strata; it possesses adaptive learning capabilities and is suitable for various environmental backgrounds: the deep model can be trained to adapt to CTD data from different sea areas, seasons, or measurement platforms, exhibiting good generalization ability, without relying on manually set parameters or prior models, significantly reducing human intervention and improving the method's versatility and adaptability; and it effectively handles data gaps and anomalies.

Provided is a conductivity temperature depth (CTD) observation information calibrating method and the CTD observation information calibrating method incudes receiving CTD observation raw information; calibrating the CTD observation raw information; and outputting calibrated CTD observation information.

The application relates to a water mass classification accuracy judgment method, which comprises the following steps: obtaining CTD observation data of a target sea area and performing standardization processing to obtain standardized data; based on a K-means++ clustering algorithm, spatial clustering analysis is performed on the standardized data with multiple element characteristics, an optimal cluster number is screened out, and the spatial distribution of the water mass is obtained; the spatial distribution of the water mass is combined with the multiple element characteristics, the three-dimensional division result of the category, spatial distribution and element characteristic range of the water mass is determined according to the optimal cluster number; and the separation degree and concentration degree of each type of water mass on the principal component space are verified according to a principal component analysis method, so as to evaluate the accuracy of the three-dimensional division result. The application realizes three-dimensional water mass classification, can comprehensively reveal the spatial structure of the water mass of the target sea area, objectively judges the classification accuracy, and effectively reduces the influence of subjective factors on the water mass division result.